针对诊断设备无备用、特征参量单一导致变电设备故障诊断可靠性和准确性较低的问题,研究了一种基于云平台的变电站设备智能诊断系统。该系统由智能传感器、诊断云平台和变电站中心控制站组成。智能传感器采集设备的实时状态数据并传输...针对诊断设备无备用、特征参量单一导致变电设备故障诊断可靠性和准确性较低的问题,研究了一种基于云平台的变电站设备智能诊断系统。该系统由智能传感器、诊断云平台和变电站中心控制站组成。智能传感器采集设备的实时状态数据并传输至云平台;云平台由智能电子设备(intelligent electronic device,IED)组成,根据任务调度原则合理分配云平台计算资源,融合初步故障诊断信息,实现故障协同诊断和诊断结果分层存储;变电站中心控制站调用高级诊断方法进一步确认故障,发出报警和维修信号。某220 k V变压器状态监测实例表明,与传统变电站诊断系统相比,该系统使IED互为冗余备用,充分利用云平台资源,并行分析状态数据,使诊断时间缩短约40.11%,提高了故障诊断的可靠性。展开更多
Intelligent connected vehicles(ICVs) are believed to change people's life in the near future by making the transportation safer,cleaner and more comfortable. Although many prototypes of ICVs have been developed to...Intelligent connected vehicles(ICVs) are believed to change people's life in the near future by making the transportation safer,cleaner and more comfortable. Although many prototypes of ICVs have been developed to prove the concept of autonomous driving and the feasibility of improving traffic efficiency, there still exists a significant gap before achieving mass production of high-level ICVs. The objective of this study is to present an overview of both the state of the art and future perspectives of key technologies that are needed for future ICVs. It is a challenging task to review all related works and predict their future perspectives, especially for such a complex and interdisciplinary area of research. This article is organized to overview the ICV key technologies by answering three questions: what are the milestones in the history of ICVs; what are the electronic components needed for building an ICV platform; and what are the essential algorithms to enable intelligent driving? To answer the first question, the article has reviewed the history and the development milestones of ICVs. For the second question, the recent technology advances in electrical/electronic architecture, sensors, and actuators are presented. For the third question, the article focuses on the algorithms in decision making, as the perception and control algorithm are covered in the development of sensors and actuators. To achieve correct decision-making, there exist two different approaches: the principle-based approach and data-driven approach. The advantages and limitations of both approaches are explained and analyzed. Currently automotive engineers are concerned more with the vehicle platform technology, whereas the academic researchers prefer to focus on theoretical algorithms. However, only by incorporating elements from both worlds can we accelerate the production of high-level ICVs.展开更多
With ever-increasing market competition and advances in technology, more and more countries are prioritizing advanced manufacturing technology as their top priority for economic growth. Germany announced the Industry ...With ever-increasing market competition and advances in technology, more and more countries are prioritizing advanced manufacturing technology as their top priority for economic growth. Germany announced the Industry 4.0 strategy in 2013. The US government launched the Advanced Manufacturing Partnership （AMP） in 2011 and the National Network for Manufacturing Innovation （NNMI） in 2014. Most recently, the Manufacturing USA initiative was officially rolled out to further ＂leverage existing resources... to nurture manufacturing innovation and accelerate commercialization＂ by fostering close collaboration between industry, academia, and government partners. In 2015, the Chinese government officially published a 10- year plan and roadmap toward manufacturing： Made in China 2025. In all these national initiatives, the core technology development and implementation is in the area of advanced manufacturing systems. A new manufacturing paradigm is emerging, which can be characterized by two unique features： integrated manufacturing and intelligent manufacturing. This trend is in line with the progress of industrial revolutions, in which higher efficiency in production systems is being continuously pursued. To this end, 10 major technologies can be identified for the new manufacturing paradigm. This paper describes the rationales and needs for integrated and intelligent manufacturing （i2M） systems. Related technologies from different fields are also described. In particular, key technological enablers, such as the Intemet of Things and Services （IoTS）, cyber-physical systems （CPSs）, and cloud computing are discussed. Challenges are addressed with applica- tions that are based on commercially available platforms such as General Electric （GE）＇s Predix and PTC＇s ThingWorx.展开更多
文摘针对诊断设备无备用、特征参量单一导致变电设备故障诊断可靠性和准确性较低的问题,研究了一种基于云平台的变电站设备智能诊断系统。该系统由智能传感器、诊断云平台和变电站中心控制站组成。智能传感器采集设备的实时状态数据并传输至云平台;云平台由智能电子设备(intelligent electronic device,IED)组成,根据任务调度原则合理分配云平台计算资源,融合初步故障诊断信息,实现故障协同诊断和诊断结果分层存储;变电站中心控制站调用高级诊断方法进一步确认故障,发出报警和维修信号。某220 k V变压器状态监测实例表明,与传统变电站诊断系统相比,该系统使IED互为冗余备用,充分利用云平台资源,并行分析状态数据,使诊断时间缩短约40.11%,提高了故障诊断的可靠性。
基金supported by the International Science and Technology Cooperation Program of China(Grant No.2016YFE0102200)the National Natural Science Foundation of China(Grant No.61773234)+1 种基金the National Key R&D Program of China(Grant No.2108YFB0105004)and Beijing Municipal Science and Technology Commission(Grant Nos.D171100005117001&D171100005117002)
文摘Intelligent connected vehicles(ICVs) are believed to change people's life in the near future by making the transportation safer,cleaner and more comfortable. Although many prototypes of ICVs have been developed to prove the concept of autonomous driving and the feasibility of improving traffic efficiency, there still exists a significant gap before achieving mass production of high-level ICVs. The objective of this study is to present an overview of both the state of the art and future perspectives of key technologies that are needed for future ICVs. It is a challenging task to review all related works and predict their future perspectives, especially for such a complex and interdisciplinary area of research. This article is organized to overview the ICV key technologies by answering three questions: what are the milestones in the history of ICVs; what are the electronic components needed for building an ICV platform; and what are the essential algorithms to enable intelligent driving? To answer the first question, the article has reviewed the history and the development milestones of ICVs. For the second question, the recent technology advances in electrical/electronic architecture, sensors, and actuators are presented. For the third question, the article focuses on the algorithms in decision making, as the perception and control algorithm are covered in the development of sensors and actuators. To achieve correct decision-making, there exist two different approaches: the principle-based approach and data-driven approach. The advantages and limitations of both approaches are explained and analyzed. Currently automotive engineers are concerned more with the vehicle platform technology, whereas the academic researchers prefer to focus on theoretical algorithms. However, only by incorporating elements from both worlds can we accelerate the production of high-level ICVs.
文摘With ever-increasing market competition and advances in technology, more and more countries are prioritizing advanced manufacturing technology as their top priority for economic growth. Germany announced the Industry 4.0 strategy in 2013. The US government launched the Advanced Manufacturing Partnership （AMP） in 2011 and the National Network for Manufacturing Innovation （NNMI） in 2014. Most recently, the Manufacturing USA initiative was officially rolled out to further ＂leverage existing resources... to nurture manufacturing innovation and accelerate commercialization＂ by fostering close collaboration between industry, academia, and government partners. In 2015, the Chinese government officially published a 10- year plan and roadmap toward manufacturing： Made in China 2025. In all these national initiatives, the core technology development and implementation is in the area of advanced manufacturing systems. A new manufacturing paradigm is emerging, which can be characterized by two unique features： integrated manufacturing and intelligent manufacturing. This trend is in line with the progress of industrial revolutions, in which higher efficiency in production systems is being continuously pursued. To this end, 10 major technologies can be identified for the new manufacturing paradigm. This paper describes the rationales and needs for integrated and intelligent manufacturing （i2M） systems. Related technologies from different fields are also described. In particular, key technological enablers, such as the Intemet of Things and Services （IoTS）, cyber-physical systems （CPSs）, and cloud computing are discussed. Challenges are addressed with applica- tions that are based on commercially available platforms such as General Electric （GE）＇s Predix and PTC＇s ThingWorx.
